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Мария Ш 2023-11-29 20:32:10 +03:00
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shestakova_maria_lab_3/README.md Normal file
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### Задание:
Часть 1. По данным о пассажирах Титаника решите задачу классификации (с помощью дерева решений), в которой по различным характеристикам пассажиров требуется найти у выживших пассажиров два наиболее важных признака из трех рассматриваемых: Pclass, Parch, Fare
Часть 2. Решите с помощью библиотечной реализации дерева решений задачу из лабораторной работы «Веб-сервис «Дерево решений» по предмету «Методы искусственного интеллекта»на 99% ваших данных: зависимость качества сна (Quality of Sleep) от возраста (Age) и пола (Gender). Проверьте работу модели на оставшемся проценте, сделайте вывод
### Технологии:
Библиотека Scikit-learn, библиотека numpy, библиотека pandas
### Что делает лабораторная:
Часть 1. Из выборки отбирается 3 необходимых по заданию признака, определяется целевая переменная по заданию, обучается дерево, выводятся важности признаков по каждому классу
Часть 2. Из выборки отбирается 2 необходимых по заданию признака, определяется целевая переменная по заданию, данные разделяются на обущающую и тестовую выборку, дерево обучается классификацией и регрессией, выводятся важности признаков, предсказания значений на тестовой выборке и оценка качества
### Как запустить:
Первая часть лабораторной работы запускается в файле `shestakova_maria_lab_3.1.py` через Run: появляется вывод в консоли
Вторая часть лабораторной работы запускается в файле `shestakova_maria_lab_3.2.py` через Run: появляется вывод в консоли
### Вывод:
Часть 1.
![img1.png](3.1.png)
Часть 2.
![img2.png](3.2.png)
По выводу можно заметить, что модель дерева классификации подходит больше для решения данной задачи

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shestakova_maria_lab_3/shestakova_maria_lab_3.1.py Normal file
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import pandas
from sklearn.tree import DecisionTreeClassifier
import numpy as np
# загрузка данных из набора
data = pandas.read_csv('titanic.csv', index_col='Passengerid')
data = data.loc[(np.isnan(data['Pclass']) == False) & (np.isnan(data['Parch']) == False) & (np.isnan(data['Fare']) == False) & (np.isnan(data['2urvived']) == False)]
# отбор по заданию
correct = data[['Pclass', 'Parch', 'Fare']]
print(correct.head())
y = data['2urvived']
# дерево решений
clf = DecisionTreeClassifier(random_state=27)
clf.fit(correct, y)
# важность признаков
important = clf.feature_importances_
print(important)

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shestakova_maria_lab_3/shestakova_maria_lab_3.2.py Normal file
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import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.tree import DecisionTreeRegressor, DecisionTreeClassifier
from sklearn.metrics import mean_squared_error
from sklearn.metrics import accuracy_score
# загрузка данных из набора
data = pd.read_csv('sleep.csv', index_col='Person ID')
# приведение строковых ячеек к числу
data['Gender'] = data['Gender'].map({'Male': 0, 'Female': 1})
# признаки (X) и целевая переменная (y)
X = data[['Age', 'Gender']]
print(X.head())
y = data['Quality of Sleep']
# обуч и тест выборка
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.01, random_state=27)
# дерево регрессии
regression_tree = DecisionTreeRegressor()
regression_tree.fit(X_train, y_train)
test_score_reg = regression_tree.score(X_test, y_test)
# важность признаков
important_reg = regression_tree.feature_importances_
# предсказание
y_pred_reg = regression_tree.predict(X_test)
# оценка модели
mse = mean_squared_error(y_test, y_pred_reg)
# дерево классификации
classifier_tree = DecisionTreeClassifier()
classifier_tree.fit(X_train, y_train)
test_score_class = classifier_tree.score(X_test, y_test)
# важность признаков
important_class = classifier_tree.feature_importances_
# предсказание
y_pred_class = classifier_tree.predict(X_test)
# оценка модели
accuracy = accuracy_score(y_test, y_pred_class)
print("Regression Tree:")
print("Score:", test_score_reg)
print("Importance:", important_reg)
print("Mean Squared Error: {:.2f}".format(mse))
print("")
print("Classification Tree:")
print("Score:", test_score_class)
print("Importance:", important_class)
print("Accuracy: {:.2f}%".format(accuracy * 100))

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shestakova_maria_lab_3/sleep.csv Normal file
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Person ID,Gender,Age,Occupation,Sleep Duration,Quality of Sleep,Physical Activity Level,Stress Level,BMI Category,Blood Pressure,Heart Rate,Daily Steps,Sleep Disorder
1,Male,27,Software Engineer,6.1,6,42,6,Overweight,126/83,77,4200,None
2,Male,28,Doctor,6.2,6,60,8,Normal,125/80,75,10000,None
3,Male,28,Doctor,6.2,6,60,8,Normal,125/80,75,10000,None
4,Male,28,Sales Representative,5.9,4,30,8,Obese,140/90,85,3000,Sleep Apnea
5,Male,28,Sales Representative,5.9,4,30,8,Obese,140/90,85,3000,Sleep Apnea
6,Male,28,Software Engineer,5.9,4,30,8,Obese,140/90,85,3000,Insomnia
7,Male,29,Teacher,6.3,6,40,7,Obese,140/90,82,3500,Insomnia
8,Male,29,Doctor,7.8,7,75,6,Normal,120/80,70,8000,None
9,Male,29,Doctor,7.8,7,75,6,Normal,120/80,70,8000,None
10,Male,29,Doctor,7.8,7,75,6,Normal,120/80,70,8000,None
11,Male,29,Doctor,6.1,6,30,8,Normal,120/80,70,8000,None
12,Male,29,Doctor,7.8,7,75,6,Normal,120/80,70,8000,None
13,Male,29,Doctor,6.1,6,30,8,Normal,120/80,70,8000,None
14,Male,29,Doctor,6,6,30,8,Normal,120/80,70,8000,None
15,Male,29,Doctor,6,6,30,8,Normal,120/80,70,8000,None
16,Male,29,Doctor,6,6,30,8,Normal,120/80,70,8000,None
17,Female,29,Nurse,6.5,5,40,7,Normal Weight,132/87,80,4000,Sleep Apnea
18,Male,29,Doctor,6,6,30,8,Normal,120/80,70,8000,Sleep Apnea
19,Female,29,Nurse,6.5,5,40,7,Normal Weight,132/87,80,4000,Insomnia
20,Male,30,Doctor,7.6,7,75,6,Normal,120/80,70,8000,None
21,Male,30,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None
22,Male,30,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None
23,Male,30,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None
24,Male,30,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None
25,Male,30,Doctor,7.8,7,75,6,Normal,120/80,70,8000,None
26,Male,30,Doctor,7.9,7,75,6,Normal,120/80,70,8000,None
27,Male,30,Doctor,7.8,7,75,6,Normal,120/80,70,8000,None
28,Male,30,Doctor,7.9,7,75,6,Normal,120/80,70,8000,None
29,Male,30,Doctor,7.9,7,75,6,Normal,120/80,70,8000,None
30,Male,30,Doctor,7.9,7,75,6,Normal,120/80,70,8000,None
31,Female,30,Nurse,6.4,5,35,7,Normal Weight,130/86,78,4100,Sleep Apnea
32,Female,30,Nurse,6.4,5,35,7,Normal Weight,130/86,78,4100,Insomnia
33,Female,31,Nurse,7.9,8,75,4,Normal Weight,117/76,69,6800,None
34,Male,31,Doctor,6.1,6,30,8,Normal,125/80,72,5000,None
35,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None
36,Male,31,Doctor,6.1,6,30,8,Normal,125/80,72,5000,None
37,Male,31,Doctor,6.1,6,30,8,Normal,125/80,72,5000,None
38,Male,31,Doctor,7.6,7,75,6,Normal,120/80,70,8000,None
39,Male,31,Doctor,7.6,7,75,6,Normal,120/80,70,8000,None
40,Male,31,Doctor,7.6,7,75,6,Normal,120/80,70,8000,None
41,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None
42,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None
43,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None
44,Male,31,Doctor,7.8,7,75,6,Normal,120/80,70,8000,None
45,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None
46,Male,31,Doctor,7.8,7,75,6,Normal,120/80,70,8000,None
47,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None
48,Male,31,Doctor,7.8,7,75,6,Normal,120/80,70,8000,None
49,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None
50,Male,31,Doctor,7.7,7,75,6,Normal,120/80,70,8000,Sleep Apnea
51,Male,32,Engineer,7.5,8,45,3,Normal,120/80,70,8000,None
52,Male,32,Engineer,7.5,8,45,3,Normal,120/80,70,8000,None
53,Male,32,Doctor,6,6,30,8,Normal,125/80,72,5000,None
54,Male,32,Doctor,7.6,7,75,6,Normal,120/80,70,8000,None
55,Male,32,Doctor,6,6,30,8,Normal,125/80,72,5000,None
56,Male,32,Doctor,6,6,30,8,Normal,125/80,72,5000,None
57,Male,32,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None
58,Male,32,Doctor,6,6,30,8,Normal,125/80,72,5000,None
59,Male,32,Doctor,6,6,30,8,Normal,125/80,72,5000,None
60,Male,32,Doctor,7.7,7,75,6,Normal,120/80,70,8000,None
61,Male,32,Doctor,6,6,30,8,Normal,125/80,72,5000,None
62,Male,32,Doctor,6,6,30,8,Normal,125/80,72,5000,None
63,Male,32,Doctor,6.2,6,30,8,Normal,125/80,72,5000,None
64,Male,32,Doctor,6.2,6,30,8,Normal,125/80,72,5000,None
65,Male,32,Doctor,6.2,6,30,8,Normal,125/80,72,5000,None
66,Male,32,Doctor,6.2,6,30,8,Normal,125/80,72,5000,None
67,Male,32,Accountant,7.2,8,50,6,Normal Weight,118/76,68,7000,None
68,Male,33,Doctor,6,6,30,8,Normal,125/80,72,5000,Insomnia
69,Female,33,Scientist,6.2,6,50,6,Overweight,128/85,76,5500,None
70,Female,33,Scientist,6.2,6,50,6,Overweight,128/85,76,5500,None
71,Male,33,Doctor,6.1,6,30,8,Normal,125/80,72,5000,None
72,Male,33,Doctor,6.1,6,30,8,Normal,125/80,72,5000,None
73,Male,33,Doctor,6.1,6,30,8,Normal,125/80,72,5000,None
74,Male,33,Doctor,6.1,6,30,8,Normal,125/80,72,5000,None
75,Male,33,Doctor,6,6,30,8,Normal,125/80,72,5000,None
76,Male,33,Doctor,6,6,30,8,Normal,125/80,72,5000,None
77,Male,33,Doctor,6,6,30,8,Normal,125/80,72,5000,None
78,Male,33,Doctor,6,6,30,8,Normal,125/80,72,5000,None
79,Male,33,Doctor,6,6,30,8,Normal,125/80,72,5000,None
80,Male,33,Doctor,6,6,30,8,Normal,125/80,72,5000,None
81,Female,34,Scientist,5.8,4,32,8,Overweight,131/86,81,5200,Sleep Apnea
82,Female,34,Scientist,5.8,4,32,8,Overweight,131/86,81,5200,Sleep Apnea
83,Male,35,Teacher,6.7,7,40,5,Overweight,128/84,70,5600,None
84,Male,35,Teacher,6.7,7,40,5,Overweight,128/84,70,5600,None
85,Male,35,Software Engineer,7.5,8,60,5,Normal Weight,120/80,70,8000,None
86,Female,35,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
87,Male,35,Engineer,7.2,8,60,4,Normal,125/80,65,5000,None
88,Male,35,Engineer,7.2,8,60,4,Normal,125/80,65,5000,None
89,Male,35,Engineer,7.3,8,60,4,Normal,125/80,65,5000,None
90,Male,35,Engineer,7.3,8,60,4,Normal,125/80,65,5000,None
91,Male,35,Engineer,7.3,8,60,4,Normal,125/80,65,5000,None
92,Male,35,Engineer,7.3,8,60,4,Normal,125/80,65,5000,None
93,Male,35,Software Engineer,7.5,8,60,5,Normal Weight,120/80,70,8000,None
94,Male,35,Lawyer,7.4,7,60,5,Obese,135/88,84,3300,Sleep Apnea
95,Female,36,Accountant,7.2,8,60,4,Normal,115/75,68,7000,Insomnia
96,Female,36,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
97,Female,36,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
98,Female,36,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
99,Female,36,Teacher,7.1,8,60,4,Normal,115/75,68,7000,None
100,Female,36,Teacher,7.1,8,60,4,Normal,115/75,68,7000,None
101,Female,36,Teacher,7.2,8,60,4,Normal,115/75,68,7000,None
102,Female,36,Teacher,7.2,8,60,4,Normal,115/75,68,7000,None
103,Female,36,Teacher,7.2,8,60,4,Normal,115/75,68,7000,None
104,Male,36,Teacher,6.6,5,35,7,Overweight,129/84,74,4800,Sleep Apnea
105,Female,36,Teacher,7.2,8,60,4,Normal,115/75,68,7000,Sleep Apnea
106,Male,36,Teacher,6.6,5,35,7,Overweight,129/84,74,4800,Insomnia
107,Female,37,Nurse,6.1,6,42,6,Overweight,126/83,77,4200,None
108,Male,37,Engineer,7.8,8,70,4,Normal Weight,120/80,68,7000,None
109,Male,37,Engineer,7.8,8,70,4,Normal Weight,120/80,68,7000,None
110,Male,37,Lawyer,7.4,8,60,5,Normal,130/85,68,8000,None
111,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
112,Male,37,Lawyer,7.4,8,60,5,Normal,130/85,68,8000,None
113,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
114,Male,37,Lawyer,7.4,8,60,5,Normal,130/85,68,8000,None
115,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
116,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
117,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
118,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
119,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
120,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
121,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
122,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
123,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
124,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
125,Female,37,Accountant,7.2,8,60,4,Normal,115/75,68,7000,None
126,Female,37,Nurse,7.5,8,60,4,Normal Weight,120/80,70,8000,None
127,Male,38,Lawyer,7.3,8,60,5,Normal,130/85,68,8000,None
128,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
129,Male,38,Lawyer,7.3,8,60,5,Normal,130/85,68,8000,None
130,Male,38,Lawyer,7.3,8,60,5,Normal,130/85,68,8000,None
131,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
132,Male,38,Lawyer,7.3,8,60,5,Normal,130/85,68,8000,None
133,Male,38,Lawyer,7.3,8,60,5,Normal,130/85,68,8000,None
134,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
135,Male,38,Lawyer,7.3,8,60,5,Normal,130/85,68,8000,None
136,Male,38,Lawyer,7.3,8,60,5,Normal,130/85,68,8000,None
137,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
138,Male,38,Lawyer,7.1,8,60,5,Normal,130/85,68,8000,None
139,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
140,Male,38,Lawyer,7.1,8,60,5,Normal,130/85,68,8000,None
141,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
142,Male,38,Lawyer,7.1,8,60,5,Normal,130/85,68,8000,None
143,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
144,Female,38,Accountant,7.1,8,60,4,Normal,115/75,68,7000,None
145,Male,38,Lawyer,7.1,8,60,5,Normal,130/85,68,8000,Sleep Apnea
146,Female,38,Lawyer,7.4,7,60,5,Obese,135/88,84,3300,Sleep Apnea
147,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,Insomnia
148,Male,39,Engineer,6.5,5,40,7,Overweight,132/87,80,4000,Insomnia
149,Female,39,Lawyer,6.9,7,50,6,Normal Weight,128/85,75,5500,None
150,Female,39,Accountant,8,9,80,3,Normal Weight,115/78,67,7500,None
151,Female,39,Accountant,8,9,80,3,Normal Weight,115/78,67,7500,None
152,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
153,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
154,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
155,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
156,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
157,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
158,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
159,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
160,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
161,Male,39,Lawyer,7.2,8,60,5,Normal,130/85,68,8000,None
162,Female,40,Accountant,7.2,8,55,6,Normal Weight,119/77,73,7300,None
163,Female,40,Accountant,7.2,8,55,6,Normal Weight,119/77,73,7300,None
164,Male,40,Lawyer,7.9,8,90,5,Normal,130/85,68,8000,None
165,Male,40,Lawyer,7.9,8,90,5,Normal,130/85,68,8000,None
166,Male,41,Lawyer,7.6,8,90,5,Normal,130/85,70,8000,Insomnia
167,Male,41,Engineer,7.3,8,70,6,Normal Weight,121/79,72,6200,None
168,Male,41,Lawyer,7.1,7,55,6,Overweight,125/82,72,6000,None
169,Male,41,Lawyer,7.1,7,55,6,Overweight,125/82,72,6000,None
170,Male,41,Lawyer,7.7,8,90,5,Normal,130/85,70,8000,None
171,Male,41,Lawyer,7.7,8,90,5,Normal,130/85,70,8000,None
172,Male,41,Lawyer,7.7,8,90,5,Normal,130/85,70,8000,None
173,Male,41,Lawyer,7.7,8,90,5,Normal,130/85,70,8000,None
174,Male,41,Lawyer,7.7,8,90,5,Normal,130/85,70,8000,None
175,Male,41,Lawyer,7.6,8,90,5,Normal,130/85,70,8000,None
176,Male,41,Lawyer,7.6,8,90,5,Normal,130/85,70,8000,None
177,Male,41,Lawyer,7.6,8,90,5,Normal,130/85,70,8000,None
178,Male,42,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
179,Male,42,Lawyer,7.8,8,90,5,Normal,130/85,70,8000,None
180,Male,42,Lawyer,7.8,8,90,5,Normal,130/85,70,8000,None
181,Male,42,Lawyer,7.8,8,90,5,Normal,130/85,70,8000,None
182,Male,42,Lawyer,7.8,8,90,5,Normal,130/85,70,8000,None
183,Male,42,Lawyer,7.8,8,90,5,Normal,130/85,70,8000,None
184,Male,42,Lawyer,7.8,8,90,5,Normal,130/85,70,8000,None
185,Female,42,Teacher,6.8,6,45,7,Overweight,130/85,78,5000,Sleep Apnea
186,Female,42,Teacher,6.8,6,45,7,Overweight,130/85,78,5000,Sleep Apnea
187,Female,43,Teacher,6.7,7,45,4,Overweight,135/90,65,6000,Insomnia
188,Male,43,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
189,Female,43,Teacher,6.7,7,45,4,Overweight,135/90,65,6000,Insomnia
190,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
191,Female,43,Teacher,6.7,7,45,4,Overweight,135/90,65,6000,Insomnia
192,Male,43,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia
193,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
194,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
195,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
196,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
197,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
198,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
199,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
200,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
201,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Insomnia
202,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,Insomnia
203,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,Insomnia
204,Male,43,Engineer,6.9,6,47,7,Normal Weight,117/76,69,6800,None
205,Male,43,Engineer,7.6,8,75,4,Overweight,122/80,68,6800,None
206,Male,43,Engineer,7.7,8,90,5,Normal,130/85,70,8000,None
207,Male,43,Engineer,7.7,8,90,5,Normal,130/85,70,8000,None
208,Male,43,Engineer,7.7,8,90,5,Normal,130/85,70,8000,None
209,Male,43,Engineer,7.7,8,90,5,Normal,130/85,70,8000,None
210,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,None
211,Male,43,Engineer,7.7,8,90,5,Normal,130/85,70,8000,None
212,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,None
213,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,None
214,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,None
215,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,None
216,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,None
217,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,None
218,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,None
219,Male,43,Engineer,7.8,8,90,5,Normal,130/85,70,8000,Sleep Apnea
220,Male,43,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,Sleep Apnea
221,Female,44,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
222,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia
223,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
224,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia
225,Female,44,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
226,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
227,Female,44,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
228,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
229,Female,44,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
230,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
231,Female,44,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
232,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
233,Female,44,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
234,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
235,Female,44,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
236,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
237,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia
238,Female,44,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia
239,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
240,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia
241,Female,44,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia
242,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
243,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,Insomnia
244,Female,44,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia
245,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
246,Female,44,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia
247,Male,44,Salesperson,6.3,6,45,7,Overweight,130/85,72,6000,Insomnia
248,Male,44,Engineer,6.8,7,45,7,Overweight,130/85,78,5000,Insomnia
249,Male,44,Salesperson,6.4,6,45,7,Overweight,130/85,72,6000,None
250,Male,44,Salesperson,6.5,6,45,7,Overweight,130/85,72,6000,None
251,Female,45,Teacher,6.8,7,30,6,Overweight,135/90,65,6000,Insomnia
252,Female,45,Teacher,6.8,7,30,6,Overweight,135/90,65,6000,Insomnia
253,Female,45,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia
254,Female,45,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia
255,Female,45,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia
256,Female,45,Teacher,6.5,7,45,4,Overweight,135/90,65,6000,Insomnia
257,Female,45,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
258,Female,45,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
259,Female,45,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
260,Female,45,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
261,Female,45,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,Insomnia
262,Female,45,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,None
263,Female,45,Teacher,6.6,7,45,4,Overweight,135/90,65,6000,None
264,Female,45,Manager,6.9,7,55,5,Overweight,125/82,75,5500,None
265,Male,48,Doctor,7.3,7,65,5,Obese,142/92,83,3500,Insomnia
266,Female,48,Nurse,5.9,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
267,Male,48,Doctor,7.3,7,65,5,Obese,142/92,83,3500,Insomnia
268,Female,49,Nurse,6.2,6,90,8,Overweight,140/95,75,10000,None
269,Female,49,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
270,Female,49,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
271,Female,49,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
272,Female,49,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
273,Female,49,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
274,Female,49,Nurse,6.2,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
275,Female,49,Nurse,6.2,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
276,Female,49,Nurse,6.2,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
277,Male,49,Doctor,8.1,9,85,3,Obese,139/91,86,3700,Sleep Apnea
278,Male,49,Doctor,8.1,9,85,3,Obese,139/91,86,3700,Sleep Apnea
279,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Insomnia
280,Female,50,Engineer,8.3,9,30,3,Normal,125/80,65,5000,None
281,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,None
282,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
283,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
284,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
285,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
286,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
287,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
288,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
289,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
290,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
291,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
292,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
293,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
294,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
295,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
296,Female,50,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
297,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
298,Female,50,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
299,Female,51,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None
300,Female,51,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None
301,Female,51,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None
302,Female,51,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None
303,Female,51,Nurse,7.1,7,55,6,Normal Weight,125/82,72,6000,None
304,Female,51,Nurse,6,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
305,Female,51,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
306,Female,51,Nurse,6.1,6,90,8,Overweight,140/95,75,10000,Sleep Apnea
307,Female,52,Accountant,6.5,7,45,7,Overweight,130/85,72,6000,Insomnia
308,Female,52,Accountant,6.5,7,45,7,Overweight,130/85,72,6000,Insomnia
309,Female,52,Accountant,6.6,7,45,7,Overweight,130/85,72,6000,Insomnia
310,Female,52,Accountant,6.6,7,45,7,Overweight,130/85,72,6000,Insomnia
311,Female,52,Accountant,6.6,7,45,7,Overweight,130/85,72,6000,Insomnia
312,Female,52,Accountant,6.6,7,45,7,Overweight,130/85,72,6000,Insomnia
313,Female,52,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None
314,Female,52,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None
315,Female,52,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None
316,Female,53,Engineer,8.3,9,30,3,Normal,125/80,65,5000,Insomnia
317,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None
318,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None
319,Female,53,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None
320,Female,53,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None
321,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None
322,Female,53,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None
323,Female,53,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None
324,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None
325,Female,53,Engineer,8.3,9,30,3,Normal,125/80,65,5000,None
326,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None
327,Female,53,Engineer,8.3,9,30,3,Normal,125/80,65,5000,None
328,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None
329,Female,53,Engineer,8.3,9,30,3,Normal,125/80,65,5000,None
330,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None
331,Female,53,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None
332,Female,53,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None
333,Female,54,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None
334,Female,54,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None
335,Female,54,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None
336,Female,54,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None
337,Female,54,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None
338,Female,54,Engineer,8.4,9,30,3,Normal,125/80,65,5000,None
339,Female,54,Engineer,8.5,9,30,3,Normal,125/80,65,5000,None
340,Female,55,Nurse,8.1,9,75,4,Overweight,140/95,72,5000,Sleep Apnea
341,Female,55,Nurse,8.1,9,75,4,Overweight,140/95,72,5000,Sleep Apnea
342,Female,56,Doctor,8.2,9,90,3,Normal Weight,118/75,65,10000,None
343,Female,56,Doctor,8.2,9,90,3,Normal Weight,118/75,65,10000,None
344,Female,57,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,None
345,Female,57,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
346,Female,57,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
347,Female,57,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
348,Female,57,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
349,Female,57,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
350,Female,57,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
351,Female,57,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
352,Female,57,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
353,Female,58,Nurse,8,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
354,Female,58,Nurse,8,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
355,Female,58,Nurse,8,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
356,Female,58,Nurse,8,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
357,Female,58,Nurse,8,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
358,Female,58,Nurse,8,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
359,Female,59,Nurse,8,9,75,3,Overweight,140/95,68,7000,None
360,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,None
361,Female,59,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
362,Female,59,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
363,Female,59,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
364,Female,59,Nurse,8.2,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
365,Female,59,Nurse,8,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
366,Female,59,Nurse,8,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
367,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
368,Female,59,Nurse,8,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
369,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
370,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
371,Female,59,Nurse,8,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
372,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
373,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
374,Female,59,Nurse,8.1,9,75,3,Overweight,140/95,68,7000,Sleep Apnea
1 Person ID Gender Age Occupation Sleep Duration Quality of Sleep Physical Activity Level Stress Level BMI Category Blood Pressure Heart Rate Daily Steps Sleep Disorder
2 1 Male 27 Software Engineer 6.1 6 42 6 Overweight 126/83 77 4200 None
3 2 Male 28 Doctor 6.2 6 60 8 Normal 125/80 75 10000 None
4 3 Male 28 Doctor 6.2 6 60 8 Normal 125/80 75 10000 None
5 4 Male 28 Sales Representative 5.9 4 30 8 Obese 140/90 85 3000 Sleep Apnea
6 5 Male 28 Sales Representative 5.9 4 30 8 Obese 140/90 85 3000 Sleep Apnea
7 6 Male 28 Software Engineer 5.9 4 30 8 Obese 140/90 85 3000 Insomnia
8 7 Male 29 Teacher 6.3 6 40 7 Obese 140/90 82 3500 Insomnia
9 8 Male 29 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
10 9 Male 29 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
11 10 Male 29 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
12 11 Male 29 Doctor 6.1 6 30 8 Normal 120/80 70 8000 None
13 12 Male 29 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
14 13 Male 29 Doctor 6.1 6 30 8 Normal 120/80 70 8000 None
15 14 Male 29 Doctor 6 6 30 8 Normal 120/80 70 8000 None
16 15 Male 29 Doctor 6 6 30 8 Normal 120/80 70 8000 None
17 16 Male 29 Doctor 6 6 30 8 Normal 120/80 70 8000 None
18 17 Female 29 Nurse 6.5 5 40 7 Normal Weight 132/87 80 4000 Sleep Apnea
19 18 Male 29 Doctor 6 6 30 8 Normal 120/80 70 8000 Sleep Apnea
20 19 Female 29 Nurse 6.5 5 40 7 Normal Weight 132/87 80 4000 Insomnia
21 20 Male 30 Doctor 7.6 7 75 6 Normal 120/80 70 8000 None
22 21 Male 30 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
23 22 Male 30 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
24 23 Male 30 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
25 24 Male 30 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
26 25 Male 30 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
27 26 Male 30 Doctor 7.9 7 75 6 Normal 120/80 70 8000 None
28 27 Male 30 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
29 28 Male 30 Doctor 7.9 7 75 6 Normal 120/80 70 8000 None
30 29 Male 30 Doctor 7.9 7 75 6 Normal 120/80 70 8000 None
31 30 Male 30 Doctor 7.9 7 75 6 Normal 120/80 70 8000 None
32 31 Female 30 Nurse 6.4 5 35 7 Normal Weight 130/86 78 4100 Sleep Apnea
33 32 Female 30 Nurse 6.4 5 35 7 Normal Weight 130/86 78 4100 Insomnia
34 33 Female 31 Nurse 7.9 8 75 4 Normal Weight 117/76 69 6800 None
35 34 Male 31 Doctor 6.1 6 30 8 Normal 125/80 72 5000 None
36 35 Male 31 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
37 36 Male 31 Doctor 6.1 6 30 8 Normal 125/80 72 5000 None
38 37 Male 31 Doctor 6.1 6 30 8 Normal 125/80 72 5000 None
39 38 Male 31 Doctor 7.6 7 75 6 Normal 120/80 70 8000 None
40 39 Male 31 Doctor 7.6 7 75 6 Normal 120/80 70 8000 None
41 40 Male 31 Doctor 7.6 7 75 6 Normal 120/80 70 8000 None
42 41 Male 31 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
43 42 Male 31 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
44 43 Male 31 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
45 44 Male 31 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
46 45 Male 31 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
47 46 Male 31 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
48 47 Male 31 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
49 48 Male 31 Doctor 7.8 7 75 6 Normal 120/80 70 8000 None
50 49 Male 31 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
51 50 Male 31 Doctor 7.7 7 75 6 Normal 120/80 70 8000 Sleep Apnea
52 51 Male 32 Engineer 7.5 8 45 3 Normal 120/80 70 8000 None
53 52 Male 32 Engineer 7.5 8 45 3 Normal 120/80 70 8000 None
54 53 Male 32 Doctor 6 6 30 8 Normal 125/80 72 5000 None
55 54 Male 32 Doctor 7.6 7 75 6 Normal 120/80 70 8000 None
56 55 Male 32 Doctor 6 6 30 8 Normal 125/80 72 5000 None
57 56 Male 32 Doctor 6 6 30 8 Normal 125/80 72 5000 None
58 57 Male 32 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
59 58 Male 32 Doctor 6 6 30 8 Normal 125/80 72 5000 None
60 59 Male 32 Doctor 6 6 30 8 Normal 125/80 72 5000 None
61 60 Male 32 Doctor 7.7 7 75 6 Normal 120/80 70 8000 None
62 61 Male 32 Doctor 6 6 30 8 Normal 125/80 72 5000 None
63 62 Male 32 Doctor 6 6 30 8 Normal 125/80 72 5000 None
64 63 Male 32 Doctor 6.2 6 30 8 Normal 125/80 72 5000 None
65 64 Male 32 Doctor 6.2 6 30 8 Normal 125/80 72 5000 None
66 65 Male 32 Doctor 6.2 6 30 8 Normal 125/80 72 5000 None
67 66 Male 32 Doctor 6.2 6 30 8 Normal 125/80 72 5000 None
68 67 Male 32 Accountant 7.2 8 50 6 Normal Weight 118/76 68 7000 None
69 68 Male 33 Doctor 6 6 30 8 Normal 125/80 72 5000 Insomnia
70 69 Female 33 Scientist 6.2 6 50 6 Overweight 128/85 76 5500 None
71 70 Female 33 Scientist 6.2 6 50 6 Overweight 128/85 76 5500 None
72 71 Male 33 Doctor 6.1 6 30 8 Normal 125/80 72 5000 None
73 72 Male 33 Doctor 6.1 6 30 8 Normal 125/80 72 5000 None
74 73 Male 33 Doctor 6.1 6 30 8 Normal 125/80 72 5000 None
75 74 Male 33 Doctor 6.1 6 30 8 Normal 125/80 72 5000 None
76 75 Male 33 Doctor 6 6 30 8 Normal 125/80 72 5000 None
77 76 Male 33 Doctor 6 6 30 8 Normal 125/80 72 5000 None
78 77 Male 33 Doctor 6 6 30 8 Normal 125/80 72 5000 None
79 78 Male 33 Doctor 6 6 30 8 Normal 125/80 72 5000 None
80 79 Male 33 Doctor 6 6 30 8 Normal 125/80 72 5000 None
81 80 Male 33 Doctor 6 6 30 8 Normal 125/80 72 5000 None
82 81 Female 34 Scientist 5.8 4 32 8 Overweight 131/86 81 5200 Sleep Apnea
83 82 Female 34 Scientist 5.8 4 32 8 Overweight 131/86 81 5200 Sleep Apnea
84 83 Male 35 Teacher 6.7 7 40 5 Overweight 128/84 70 5600 None
85 84 Male 35 Teacher 6.7 7 40 5 Overweight 128/84 70 5600 None
86 85 Male 35 Software Engineer 7.5 8 60 5 Normal Weight 120/80 70 8000 None
87 86 Female 35 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
88 87 Male 35 Engineer 7.2 8 60 4 Normal 125/80 65 5000 None
89 88 Male 35 Engineer 7.2 8 60 4 Normal 125/80 65 5000 None
90 89 Male 35 Engineer 7.3 8 60 4 Normal 125/80 65 5000 None
91 90 Male 35 Engineer 7.3 8 60 4 Normal 125/80 65 5000 None
92 91 Male 35 Engineer 7.3 8 60 4 Normal 125/80 65 5000 None
93 92 Male 35 Engineer 7.3 8 60 4 Normal 125/80 65 5000 None
94 93 Male 35 Software Engineer 7.5 8 60 5 Normal Weight 120/80 70 8000 None
95 94 Male 35 Lawyer 7.4 7 60 5 Obese 135/88 84 3300 Sleep Apnea
96 95 Female 36 Accountant 7.2 8 60 4 Normal 115/75 68 7000 Insomnia
97 96 Female 36 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
98 97 Female 36 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
99 98 Female 36 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
100 99 Female 36 Teacher 7.1 8 60 4 Normal 115/75 68 7000 None
101 100 Female 36 Teacher 7.1 8 60 4 Normal 115/75 68 7000 None
102 101 Female 36 Teacher 7.2 8 60 4 Normal 115/75 68 7000 None
103 102 Female 36 Teacher 7.2 8 60 4 Normal 115/75 68 7000 None
104 103 Female 36 Teacher 7.2 8 60 4 Normal 115/75 68 7000 None
105 104 Male 36 Teacher 6.6 5 35 7 Overweight 129/84 74 4800 Sleep Apnea
106 105 Female 36 Teacher 7.2 8 60 4 Normal 115/75 68 7000 Sleep Apnea
107 106 Male 36 Teacher 6.6 5 35 7 Overweight 129/84 74 4800 Insomnia
108 107 Female 37 Nurse 6.1 6 42 6 Overweight 126/83 77 4200 None
109 108 Male 37 Engineer 7.8 8 70 4 Normal Weight 120/80 68 7000 None
110 109 Male 37 Engineer 7.8 8 70 4 Normal Weight 120/80 68 7000 None
111 110 Male 37 Lawyer 7.4 8 60 5 Normal 130/85 68 8000 None
112 111 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
113 112 Male 37 Lawyer 7.4 8 60 5 Normal 130/85 68 8000 None
114 113 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
115 114 Male 37 Lawyer 7.4 8 60 5 Normal 130/85 68 8000 None
116 115 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
117 116 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
118 117 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
119 118 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
120 119 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
121 120 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
122 121 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
123 122 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
124 123 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
125 124 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
126 125 Female 37 Accountant 7.2 8 60 4 Normal 115/75 68 7000 None
127 126 Female 37 Nurse 7.5 8 60 4 Normal Weight 120/80 70 8000 None
128 127 Male 38 Lawyer 7.3 8 60 5 Normal 130/85 68 8000 None
129 128 Female 38 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
130 129 Male 38 Lawyer 7.3 8 60 5 Normal 130/85 68 8000 None
131 130 Male 38 Lawyer 7.3 8 60 5 Normal 130/85 68 8000 None
132 131 Female 38 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
133 132 Male 38 Lawyer 7.3 8 60 5 Normal 130/85 68 8000 None
134 133 Male 38 Lawyer 7.3 8 60 5 Normal 130/85 68 8000 None
135 134 Female 38 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
136 135 Male 38 Lawyer 7.3 8 60 5 Normal 130/85 68 8000 None
137 136 Male 38 Lawyer 7.3 8 60 5 Normal 130/85 68 8000 None
138 137 Female 38 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
139 138 Male 38 Lawyer 7.1 8 60 5 Normal 130/85 68 8000 None
140 139 Female 38 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
141 140 Male 38 Lawyer 7.1 8 60 5 Normal 130/85 68 8000 None
142 141 Female 38 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
143 142 Male 38 Lawyer 7.1 8 60 5 Normal 130/85 68 8000 None
144 143 Female 38 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
145 144 Female 38 Accountant 7.1 8 60 4 Normal 115/75 68 7000 None
146 145 Male 38 Lawyer 7.1 8 60 5 Normal 130/85 68 8000 Sleep Apnea
147 146 Female 38 Lawyer 7.4 7 60 5 Obese 135/88 84 3300 Sleep Apnea
148 147 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 Insomnia
149 148 Male 39 Engineer 6.5 5 40 7 Overweight 132/87 80 4000 Insomnia
150 149 Female 39 Lawyer 6.9 7 50 6 Normal Weight 128/85 75 5500 None
151 150 Female 39 Accountant 8 9 80 3 Normal Weight 115/78 67 7500 None
152 151 Female 39 Accountant 8 9 80 3 Normal Weight 115/78 67 7500 None
153 152 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
154 153 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
155 154 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
156 155 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
157 156 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
158 157 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
159 158 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
160 159 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
161 160 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
162 161 Male 39 Lawyer 7.2 8 60 5 Normal 130/85 68 8000 None
163 162 Female 40 Accountant 7.2 8 55 6 Normal Weight 119/77 73 7300 None
164 163 Female 40 Accountant 7.2 8 55 6 Normal Weight 119/77 73 7300 None
165 164 Male 40 Lawyer 7.9 8 90 5 Normal 130/85 68 8000 None
166 165 Male 40 Lawyer 7.9 8 90 5 Normal 130/85 68 8000 None
167 166 Male 41 Lawyer 7.6 8 90 5 Normal 130/85 70 8000 Insomnia
168 167 Male 41 Engineer 7.3 8 70 6 Normal Weight 121/79 72 6200 None
169 168 Male 41 Lawyer 7.1 7 55 6 Overweight 125/82 72 6000 None
170 169 Male 41 Lawyer 7.1 7 55 6 Overweight 125/82 72 6000 None
171 170 Male 41 Lawyer 7.7 8 90 5 Normal 130/85 70 8000 None
172 171 Male 41 Lawyer 7.7 8 90 5 Normal 130/85 70 8000 None
173 172 Male 41 Lawyer 7.7 8 90 5 Normal 130/85 70 8000 None
174 173 Male 41 Lawyer 7.7 8 90 5 Normal 130/85 70 8000 None
175 174 Male 41 Lawyer 7.7 8 90 5 Normal 130/85 70 8000 None
176 175 Male 41 Lawyer 7.6 8 90 5 Normal 130/85 70 8000 None
177 176 Male 41 Lawyer 7.6 8 90 5 Normal 130/85 70 8000 None
178 177 Male 41 Lawyer 7.6 8 90 5 Normal 130/85 70 8000 None
179 178 Male 42 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
180 179 Male 42 Lawyer 7.8 8 90 5 Normal 130/85 70 8000 None
181 180 Male 42 Lawyer 7.8 8 90 5 Normal 130/85 70 8000 None
182 181 Male 42 Lawyer 7.8 8 90 5 Normal 130/85 70 8000 None
183 182 Male 42 Lawyer 7.8 8 90 5 Normal 130/85 70 8000 None
184 183 Male 42 Lawyer 7.8 8 90 5 Normal 130/85 70 8000 None
185 184 Male 42 Lawyer 7.8 8 90 5 Normal 130/85 70 8000 None
186 185 Female 42 Teacher 6.8 6 45 7 Overweight 130/85 78 5000 Sleep Apnea
187 186 Female 42 Teacher 6.8 6 45 7 Overweight 130/85 78 5000 Sleep Apnea
188 187 Female 43 Teacher 6.7 7 45 4 Overweight 135/90 65 6000 Insomnia
189 188 Male 43 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
190 189 Female 43 Teacher 6.7 7 45 4 Overweight 135/90 65 6000 Insomnia
191 190 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
192 191 Female 43 Teacher 6.7 7 45 4 Overweight 135/90 65 6000 Insomnia
193 192 Male 43 Salesperson 6.4 6 45 7 Overweight 130/85 72 6000 Insomnia
194 193 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
195 194 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
196 195 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
197 196 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
198 197 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
199 198 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
200 199 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
201 200 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
202 201 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Insomnia
203 202 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 Insomnia
204 203 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 Insomnia
205 204 Male 43 Engineer 6.9 6 47 7 Normal Weight 117/76 69 6800 None
206 205 Male 43 Engineer 7.6 8 75 4 Overweight 122/80 68 6800 None
207 206 Male 43 Engineer 7.7 8 90 5 Normal 130/85 70 8000 None
208 207 Male 43 Engineer 7.7 8 90 5 Normal 130/85 70 8000 None
209 208 Male 43 Engineer 7.7 8 90 5 Normal 130/85 70 8000 None
210 209 Male 43 Engineer 7.7 8 90 5 Normal 130/85 70 8000 None
211 210 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 None
212 211 Male 43 Engineer 7.7 8 90 5 Normal 130/85 70 8000 None
213 212 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 None
214 213 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 None
215 214 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 None
216 215 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 None
217 216 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 None
218 217 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 None
219 218 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 None
220 219 Male 43 Engineer 7.8 8 90 5 Normal 130/85 70 8000 Sleep Apnea
221 220 Male 43 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 Sleep Apnea
222 221 Female 44 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
223 222 Male 44 Salesperson 6.4 6 45 7 Overweight 130/85 72 6000 Insomnia
224 223 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
225 224 Male 44 Salesperson 6.4 6 45 7 Overweight 130/85 72 6000 Insomnia
226 225 Female 44 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
227 226 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
228 227 Female 44 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
229 228 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
230 229 Female 44 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
231 230 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
232 231 Female 44 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
233 232 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
234 233 Female 44 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
235 234 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
236 235 Female 44 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
237 236 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
238 237 Male 44 Salesperson 6.4 6 45 7 Overweight 130/85 72 6000 Insomnia
239 238 Female 44 Teacher 6.5 7 45 4 Overweight 135/90 65 6000 Insomnia
240 239 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
241 240 Male 44 Salesperson 6.4 6 45 7 Overweight 130/85 72 6000 Insomnia
242 241 Female 44 Teacher 6.5 7 45 4 Overweight 135/90 65 6000 Insomnia
243 242 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
244 243 Male 44 Salesperson 6.4 6 45 7 Overweight 130/85 72 6000 Insomnia
245 244 Female 44 Teacher 6.5 7 45 4 Overweight 135/90 65 6000 Insomnia
246 245 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
247 246 Female 44 Teacher 6.5 7 45 4 Overweight 135/90 65 6000 Insomnia
248 247 Male 44 Salesperson 6.3 6 45 7 Overweight 130/85 72 6000 Insomnia
249 248 Male 44 Engineer 6.8 7 45 7 Overweight 130/85 78 5000 Insomnia
250 249 Male 44 Salesperson 6.4 6 45 7 Overweight 130/85 72 6000 None
251 250 Male 44 Salesperson 6.5 6 45 7 Overweight 130/85 72 6000 None
252 251 Female 45 Teacher 6.8 7 30 6 Overweight 135/90 65 6000 Insomnia
253 252 Female 45 Teacher 6.8 7 30 6 Overweight 135/90 65 6000 Insomnia
254 253 Female 45 Teacher 6.5 7 45 4 Overweight 135/90 65 6000 Insomnia
255 254 Female 45 Teacher 6.5 7 45 4 Overweight 135/90 65 6000 Insomnia
256 255 Female 45 Teacher 6.5 7 45 4 Overweight 135/90 65 6000 Insomnia
257 256 Female 45 Teacher 6.5 7 45 4 Overweight 135/90 65 6000 Insomnia
258 257 Female 45 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
259 258 Female 45 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
260 259 Female 45 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
261 260 Female 45 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
262 261 Female 45 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 Insomnia
263 262 Female 45 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 None
264 263 Female 45 Teacher 6.6 7 45 4 Overweight 135/90 65 6000 None
265 264 Female 45 Manager 6.9 7 55 5 Overweight 125/82 75 5500 None
266 265 Male 48 Doctor 7.3 7 65 5 Obese 142/92 83 3500 Insomnia
267 266 Female 48 Nurse 5.9 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
268 267 Male 48 Doctor 7.3 7 65 5 Obese 142/92 83 3500 Insomnia
269 268 Female 49 Nurse 6.2 6 90 8 Overweight 140/95 75 10000 None
270 269 Female 49 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
271 270 Female 49 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
272 271 Female 49 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
273 272 Female 49 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
274 273 Female 49 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
275 274 Female 49 Nurse 6.2 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
276 275 Female 49 Nurse 6.2 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
277 276 Female 49 Nurse 6.2 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
278 277 Male 49 Doctor 8.1 9 85 3 Obese 139/91 86 3700 Sleep Apnea
279 278 Male 49 Doctor 8.1 9 85 3 Obese 139/91 86 3700 Sleep Apnea
280 279 Female 50 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Insomnia
281 280 Female 50 Engineer 8.3 9 30 3 Normal 125/80 65 5000 None
282 281 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 None
283 282 Female 50 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
284 283 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
285 284 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
286 285 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
287 286 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
288 287 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
289 288 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
290 289 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
291 290 Female 50 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
292 291 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
293 292 Female 50 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
294 293 Female 50 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
295 294 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
296 295 Female 50 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
297 296 Female 50 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
298 297 Female 50 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
299 298 Female 50 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
300 299 Female 51 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
301 300 Female 51 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
302 301 Female 51 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
303 302 Female 51 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
304 303 Female 51 Nurse 7.1 7 55 6 Normal Weight 125/82 72 6000 None
305 304 Female 51 Nurse 6 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
306 305 Female 51 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
307 306 Female 51 Nurse 6.1 6 90 8 Overweight 140/95 75 10000 Sleep Apnea
308 307 Female 52 Accountant 6.5 7 45 7 Overweight 130/85 72 6000 Insomnia
309 308 Female 52 Accountant 6.5 7 45 7 Overweight 130/85 72 6000 Insomnia
310 309 Female 52 Accountant 6.6 7 45 7 Overweight 130/85 72 6000 Insomnia
311 310 Female 52 Accountant 6.6 7 45 7 Overweight 130/85 72 6000 Insomnia
312 311 Female 52 Accountant 6.6 7 45 7 Overweight 130/85 72 6000 Insomnia
313 312 Female 52 Accountant 6.6 7 45 7 Overweight 130/85 72 6000 Insomnia
314 313 Female 52 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
315 314 Female 52 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
316 315 Female 52 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
317 316 Female 53 Engineer 8.3 9 30 3 Normal 125/80 65 5000 Insomnia
318 317 Female 53 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
319 318 Female 53 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
320 319 Female 53 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
321 320 Female 53 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
322 321 Female 53 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
323 322 Female 53 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
324 323 Female 53 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
325 324 Female 53 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
326 325 Female 53 Engineer 8.3 9 30 3 Normal 125/80 65 5000 None
327 326 Female 53 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
328 327 Female 53 Engineer 8.3 9 30 3 Normal 125/80 65 5000 None
329 328 Female 53 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
330 329 Female 53 Engineer 8.3 9 30 3 Normal 125/80 65 5000 None
331 330 Female 53 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
332 331 Female 53 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
333 332 Female 53 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
334 333 Female 54 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
335 334 Female 54 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
336 335 Female 54 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
337 336 Female 54 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
338 337 Female 54 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
339 338 Female 54 Engineer 8.4 9 30 3 Normal 125/80 65 5000 None
340 339 Female 54 Engineer 8.5 9 30 3 Normal 125/80 65 5000 None
341 340 Female 55 Nurse 8.1 9 75 4 Overweight 140/95 72 5000 Sleep Apnea
342 341 Female 55 Nurse 8.1 9 75 4 Overweight 140/95 72 5000 Sleep Apnea
343 342 Female 56 Doctor 8.2 9 90 3 Normal Weight 118/75 65 10000 None
344 343 Female 56 Doctor 8.2 9 90 3 Normal Weight 118/75 65 10000 None
345 344 Female 57 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 None
346 345 Female 57 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
347 346 Female 57 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
348 347 Female 57 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
349 348 Female 57 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
350 349 Female 57 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
351 350 Female 57 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
352 351 Female 57 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
353 352 Female 57 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
354 353 Female 58 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
355 354 Female 58 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
356 355 Female 58 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
357 356 Female 58 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
358 357 Female 58 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
359 358 Female 58 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
360 359 Female 59 Nurse 8 9 75 3 Overweight 140/95 68 7000 None
361 360 Female 59 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 None
362 361 Female 59 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
363 362 Female 59 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
364 363 Female 59 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
365 364 Female 59 Nurse 8.2 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
366 365 Female 59 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
367 366 Female 59 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
368 367 Female 59 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
369 368 Female 59 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
370 369 Female 59 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
371 370 Female 59 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
372 371 Female 59 Nurse 8 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
373 372 Female 59 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
374 373 Female 59 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea
375 374 Female 59 Nurse 8.1 9 75 3 Overweight 140/95 68 7000 Sleep Apnea

1310
shestakova_maria_lab_3/titanic.csv Normal file
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